BUSMHR HUMAN RESOURCE ANALYTICS (3 Credit Hours) SPRING 2018 CLASS SCHEDULE: Tuesday/Thursday 11:10AM-12:30AM LOCATION: Mason Hall 405

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1 BUSMHR HUMAN RESOURCE ANALYTICS (3 Credit Hours) SPRING 2018 CLASS SCHEDULE: Tuesday/Thursday 11:10AM-12:30AM LOCATION: Mason Hall 405 Instructor: Dr. Kaifeng Jiang Office: 750 Fisher Hall Phone: Website: kaifengjiangshrm.com Office Hours: By appointment Course Overview: HRM plays an increasingly important role in helping organizations achieve sustainable competitive advantage by managing human capital and human resources. In order to optimize organizational efficiency and improve decisions about human capital and organizations as a whole, the new-style HR professional need to know how to systematically collect, analyze, and interpret data of HRM. This course is intended to prepare you with the necessary tools for using data analysis to inform HR decisionmaking and to analyze issues and problems in HRM. The course starts with an introduction to HR analytics and the theoretical foundations of HRM. Then it teaches the analytic tools including both theoretical (e.g., theoretical models and frameworks) and empirical analyses (e.g., descriptive statistics and statistical inference), which will be applied to decisions in core HR areas, such as workforce planning, staffing, selection, training, performance appraisal, compensation, and HRM systems. This course emphasizes identifying appropriate analytic techniques for solving a variety of HR problems. Students will use data and statistical tools to evaluate and make recommendations for HR policies and practices. Learning Goals: The overall objective of this course is to familiarize the students with HR analytics and its applicability in HRM. Some specific objectives are: To understand the value of analytics for use in solving HR problems; To develop critical thinking skills to identify questions that can be answered with an HR dataset; To learn basic and advanced statistical analysis and know how to apply appropriate methods to improve HR decision-making; To apply statistical software (e.g., Excel and SPSS) to manipulate and organize data for analysis; Effectively interpret and communicate results from statistical analysis into actionable HR decisions. Kaifeng Jiang HR Analytics Spring

2 Teaching Philosophy and Class Value: My primary goal is to create a positive and constructive learning environment where everyone is engaged and welcome to speak up. Learning is an active process. Researchers have found that the best way to learn is by doing. As Confucius once said, "Tell me, and I will forget. Show me, and I may remember. Involve me, and I will understand" (Confucius circa 450 BC). The following points summarize our mutual expectations for this course: Mutual respect Honesty High standards Openness Positive tone Team spirits Course Materials: Lepak, D. P. & Gowan, M Human Resource Management: Managing Employees for Competitive Advantage, 3 rd Edition. Publisher: Chicago, IL: Chicago Business Press. (The earlier edition of this textbook is also acceptable) ISBN: Edwards, M. R., & Edwards, K Predictive HR Analytics: Mastering the HR Metric. Publisher: KoganPage. ISBN: We will learn how to use Excel and SPSS to analyze data. I assume Excel has already installed in your computer. Please download SPSS from CIO s website (for Windows for Mac OS If you need any assistant, please contact me or the CIO office. Additional readings, slides, assignments, and datasets will be uploaded to Carmen course website will be used to upload course materials, make course-related announcements, and assign grades. Course Requirements: Your grade for this class will be based on your performance on two exams, a group project presentation and a group report, two group assignments, one HR Analytics In The News group presentation, and class attendance and participation. Kaifeng Jiang HR Analytics Spring

3 Grading Items % Overall Points Mid-Term Exam 20% Final Exam 30% HR Analytics In The News Presentation 5% Pick-One Research Paper Summary 5% Participation 10% Group Presentation 10% Group Report 10% Group Assignments 5% for each, and 10% in total Grading Scale: Letter Percentage Scale A A B B B C C C D D E Kaifeng Jiang HR Analytics Spring

4 Exams Individual Work Two exam will be arranged, including one mid-term exam (Thursday, March 1, in class) and one accumulative final exam (Monday, April 30, 10:00-11:45AM, Location to be determined). Although somewhat outdated, written exam is still regarded as one of the most effective and widely used ways for learning evaluation. The purpose of these exams is not to ask you memorize the definitions of concepts and methods learned in class, but test your understanding of these knowledge points and help you to learn to apply these concepts to explain different management phenomenon. Basic Requirements: They are written exams and should be completed alone. Exams are to be taken during assigned times (please see the specific location and time below). None of the course-related materials are allowed to take to the exams. The exam is consisted of multiple-choice questions, case questions, and essay questions. Content of the exams come from lectures, textbook, class discussion, and assigned readings and exercises. Make-up exams will only be given to those who had emergencies and had reported to me a written reason in advance. If you have an unexcused absence from an exam, you will only be able to retake the test for 60% credit. HR Analytics In The News Presentation From Week 7 to Week 14, there will be a dedicated portion to topics In The News in Tuesday s class. This portion of the course is geared to provide students with a chance to understand the application of HR analytics in real business world. Basic Requirement: Students need to be prepared to present an example in the news that is relevant for the topic of that class period. For example, we will discuss how to use data analytics for recruitment and selection in Week 7. Students may find news about how companies use data analytics to select employees. (e.g., Students should be prepared to distribute relevant reading materials from In The News (e.g., publications, online article, etc.) to the class in the week before their presentation. You can use the Forums function on Carmen to upload and share the materials with the class. Make a 5-10 minute presentation regarding their topic to introduce the background of the issue they identify from the recent news as well as the general findings from research. Lead a discussion about the implications of the topic for HR analytics. Evaluation Criteria: In-The-News presentation will be evaluated on the following aspects. Kaifeng Jiang HR Analytics Spring

5 The extent to which a student clearly introduces the topic and the issue he or she identifies. The extent to which a presentation covers the main idea of the practical article and main findings of the research article. The extent to which a student relates the issue to course concepts and knowledge. The extent to which a student provides implications to managerial practices. The extent to which a student successfully leads the class discussion. The extent to which a student offers insightful opinions and suggestions based on the class discussion. Pick-One Research Paper Summary (Due: April 5) For this individual assignment, each student will select one of the articles identified in the optional reading list (see Carmen website) to summarize the key information of the article and discuss the findings of the article. The purpose of this assignment is to help students understand how to link research findings with managerial practices and how to use scientific evidence to help make management decisions. Basic requirements: Turn in a two-page (single spaced, 1-inch margins) summary for the article you pick. In the summary, you are expected to answer the following questions: o What is the purpose of the research reported in the article? o How does the research relate to one or more of the topics covered in class? o What are the major findings of this article? Include a brief description of the methods used to test the research hypotheses. o What are the practical implications of the research findings for the field of HRM? o Do you think the findings of the article are out-of-date? If so, consider how the findings would change in today s business environment. Participation As a class member, you are responsible for helping to create a positive, learning environment. This means listening attentively to others, sharing your own views and experiences, bringing in relevant current information, and in general contributing to our learning process. Dysfunctional participation, such as the use of cell phones, side conversations, and frequent tardiness or absence also detracts from the experience of everyone in our class. Basic Requirements: Be prepared by being familiar with readings and being ready to discuss class topics. Visible participation such as making comments is important as well as less obvious participation such as listening and being engaged in class activities. When appropriate, bridge your comments with other classmates points and questions. Kaifeng Jiang HR Analytics Spring

6 Take responsibility for yourself and for getting the information you need to succeed. Be punctual. Act in ways that connote goodwill toward the class. Be especially respectful of viewpoints and backgrounds that might differ from your own. The wise learner listens even more intently to positions that differ from his or her own. Participation does not mean sharing every single idea that occurs to you, disrespecting others comments, or dominating the discussion. As a general rule quality of contribution will always be rated higher than quantity of contribution. Evaluation Criteria: Points Outstanding participation Excellent participation Good participation Fair participation Poor participation Criteria Participate enthusiastically and contribute actively in all class discussion, exercises, and activities. Share insights of relevant information from reading, learning, and personal experience. Demonstrate outstanding capability to apply and analyze course material. Make insightful comments to move discussion forward rather than repeat what others have said. Comply with course policies all the time. Make a significant contribution to almost all class discussion, exercises, and activities. Demonstrate capability to analyze and apply course material. Almost never miss class. Comply with course policies all the time. Participate regularly and voluntarily in class discussions. Contribute relevant and important points to topics of discussion. Always attend class and only miss class with prior notification to the instructor. Comply with course policies all the time. Attend class regularly, but miss more classes than others in the course. Demonstrate sporadic participation in class activities. Always comply with course policies. Demonstrate consistently poor attendance and poor preparation. Consistently fail to participate in class activities. Fail to contribute in class, even when called upon. Behave in manner that is disruptive to the class. Sometimes violate course policies. I understand that everyone has different personalities, and as we will learn in class, introverted people may be reluctant to speak up in front of strangers (but may talk a lot to Kaifeng Jiang HR Analytics Spring

7 people they feel comfortable with). My role is to create a positive learning environment in which everyone feels psychologically safe and comfortable to speak up. I will observe each of you over the course of the semester and will make a judgment if you ve tried your best in participating in class. If you still feel any barrier or obstacle to participate, please stop by during my office hours so that we can discuss your participation and how it can be improved. Group Assignments Group Work The purpose of group assignment is to provide opportunities for students to practice how to collect, analyze, and interpret data to solve HR problems and prepare them for their final group project. Assignment 1: What s the evidence? Presentation (Due: January 30) Check out whether scientific evidence exists for the effectiveness of a popular management practice. We will choose one in class (e.g., Balanced Scorecard, 360 feedback, SWOT analysis, McKinsey s 7S model, Porter s 5 Forces, etc.). Use EBSCO, ABIinform or Google Scholar synced to a university library e-data bases. Search only PEER REVIEWED articles (check that box on the Search page) Try to find at least five papers related to the practice. Give a 15-minute presentation of how you searched, the articles you found, and what conclusions you draw from their findings. In the presentation, o Introduce the management practice you choose and explain its popularity in organizations. o Explain how you search for academic research to examine the effectiveness of this practice. o Indicate your answer to the question Is there evidence that the practice or model is likely to be effective or useful? Tell us how you arrived at this conclusion. o Give implications to the use of this practice in organizations in the future. Assignment 2: Design an Attitudinal Survey Written Report (Due: March 22) Based on the lecture and reading materials on Measurements and research designs (Jan 23): Choose a variable that interests you (e.g., customer satisfaction, employee engagement, job satisfaction, training reactions, organizational efficiency, leadership effectiveness, and work climate), that you believe lends itself well to assessment via a survey. Develop a set of at least 20 survey questions designed to measure this variable. Discuss your survey with at least three working employees outside of the class. Ask them to read your questions and write down all the thoughts they have about responding to them. The goal is to identify ambiguities or difficulties respondents may have in answering the questions. Revise your survey items based on the feedback you receive. Kaifeng Jiang HR Analytics Spring

8 Write a short report (3 pages maximum, double-spaced, without appendix): o What is the variable you intend to measure with your survey? o Why do you believe a survey is an appropriate way to assess this construct? What are the shortcomings of this approach? o Why do you come up with the survey questions for this variable? o How are those questions revised or updated after you receive the feedback from working employees? o How could a company use your survey to assess and improve their management practices? o Submit a copy of your original survey items and a final copy after revision in an Appendix. Group Project Presentation & Report The primary goal of final group project is twofold: 1) to apply analytical knowledge and skills learned in class to explain management reality; 2) to practice teamwork, communication, problem solving, data analysis, and writing skills. Basic Requirements: Teams are required to design research to answer questions about a specific HRM practice of their choice. Below are some sample questions that you might consider Of course you are not limited to this list! (Determine your research question by February 1 st ) o What practices can be used to attract more job applicants? o What factors can help predict salesperson s job performance? o What factors can lead to interview opportunities or job offers? o Will comparative and absolute performance appraisals have different influences on employee attitudes and behaviors? o How will the use of technology influence the effectiveness of training? o What factors can help reduce employment discrimination in organizations? o How will the open and secret pay policies influence employee fairness perception? o What factors can predict the starting salaries of MBA students? Team work with the instructor to polish their research ideas and develop datacollection plans to test their ideas in the first half of the semester (Due: February 22 nd ). Teams collect their own data based on the confirmed research model from students or working employees to test their research idea and work with the instructor to discuss their research findings before the final presentations (Due: March 29 th ). Teams are required to use basic statistical techniques in data analysis (e.g., ANOVA, correlation, and regression) and prepare final presentation (Due: April 12) and written paper (Due: April 19). Kaifeng Jiang HR Analytics Spring

9 Evaluation Criteria: Group presentation: Each team needs to give a 20-minute presentation in class. All team members are required to show up for the presentation. Group presentation will be evaluated according to the following criteria: Introduction: the purpose of the presentation needs to be clear. Structure: the format of the presentation is flexible, but needs to be wellstructured with logical line of reasoning, clear transitions among sections, and a clear conclusion. Analysis: Statistical methods are appropriate to test research ideas and the presentation of results is clear. Evaluation: The team draws appropriate conclusions from research findings and offers relevant implications to organizational practices. Delivery: Presenters speak clearly and stay within the allotted time. Visual aids: PowerPoint slides are carefully prepared and synchronized with the oral presentation. Discussion: Questions are answered clearly and effectively. Written report: The written report should be a 15-page long paper (excluding title page, abstract, tables, figures, and references; double spaced, 1-inch margins). The report will be evaluated based on the following criteria: Have a clear introduction of research question (e.g., what the questions is and why it is important?) Have a thorough explanation for the relationships hypothesized in the research model (e.g., use the concepts/knowledge points learned in class or literature search to support the arguments). Describe the procedure used to collect data and the basic information of the sample (e.g., total number of individuals, average age, and percent of female). Report analytic strategy and results in a rigorous way. Make effective suggestions and implications based on research findings. Demonstrate substantial depth and fullness of thought in the suggestions. Show clear, focused, and coherent organization. Structure the paper well and exhibit smooth transition between sections. Be sure to follow American Psychological Association (APA) format. See the citing sources offered by OSU libraries ( Kaifeng Jiang HR Analytics Spring

10 Other Important Course Policies Use of electronic devices Experience (and many other professors) has taught me that students who use their cell phones during class tend to be less engaged in the course and perform less effectively than students who devote their full attention to the classroom experience. Please turn off cell phones during class. Students are allowed to use laptops when they need to analyze data during the class time. Attendance While I do not formally require attendance, it is highly recommended. Given the cumulative nature of the class, falling behind on lectures will impair your learning of new statistical concepts based upon prior material. If you must miss class, be sure to get a copy of the class notes from a reliable classmate. Late Work Assignments will be graded down 10% after their specific deadlines, and 10% for each additional day they are late. Exceptions to this rule will be considered only for unusual circumstances. Office Hour Policy While I will be in my office during my office hours, sometimes I may be called away, and perhaps the times do not work for you, or perhaps some of you want to meet me at the same time. So if you would like to meet me, please me in advance so that I can make an arrangement. OSU Disability Policy The University strives to make all learning experiences as accessible as possible. If you anticipate or experience academic barriers based on your disability (including mental health, chronic or temporary medical conditions), please let me know immediately so that we can privately discuss options. You are also welcome to register with Student Life Disability Services to establish reasonable accommodations. After registration, make arrangements with me as soon as possible to discuss your accommodations so that they may be implemented in a timely fashion. SLDS contact information: slds@osu.edu; ; slds.osu.edu; 098 Baker Hall, 113 W. 12th Avenue. Academic Misconduct The Ohio State University s Code of Student Conduct, Section defines academic misconduct as: Any activity that tends to compromise the academic integrity of the University, or subvert the educational process. Examples of academic misconduct include (but are not limited to) plagiarism, collusion (unauthorized collaboration), Kaifeng Jiang HR Analytics Spring

11 copying the work of another student, and possession of unauthorized materials during an examination. Ignorance of the University s Code of Student Conduct is never considered an excuse for academic misconduct. The Ohio State University and the Committee on Academic Misconduct (COAM) expect that all students have read and understand the University s Code of Student Conduct, and that all students will complete all academic and scholarly assignments with fairness and honesty. Failure to follow the rules and guidelines established in the University s Code of Student Conduct may constitute Academic Misconduct. Sanctions for the misconduct could include a failing grade in this course and suspension or dismissal from the University. For more information, please reference: Kaifeng Jiang HR Analytics Spring

12 SPRING 2018 COURSE SCHEDULE, TOPICS, ASSIGNMENTS, EXAMS Note: This schedule may be subject to change. WEEK DATE MATERIAL COVERED DETAILS 1 Jan 9 Introduction Data analytics and HRM Ch 1 of E&E s book Jan 11 Theoretical foundations of HRM Part I Ch1 of L&G s book 2 Jan 16 Theoretical foundations of HRM Part II Ch 2 of L&G s book Jan 18 Theoretical foundations of HRM Part III Ch 14 of L&G s book 3 Jan 23 Analytical foundations of HRM Measurements and research Ch 3 of E&E s book designs Jan 25 Analytical foundations of HRM Descriptive statistics and Ch 3 of E&E s book inferential statistics 4 Jan 30 Presentations for 1 st Group Assignment 1 st Group assignment due Feb 1 Analytical foundations of HRM Mean comparison Final group project topic due 5 Feb 6 Analytical foundations of HRM Correlation Ch 3 of E&E s book Feb 8 Analytical foundations of HRM Single regression Ch 3 of E&E s book 6 Feb 13 Analytical foundations of HRM Multiple regression Ch 3 of E&E s book Feb 15 Analytical foundations of HRM Mediation and Moderation p of E&E s book Feb 20 Ch 6-7 of L&G s book 7 Ch 8 of E&E s book Recruitment and selection analytics Feb 22 Data collection plan for final group project due 8 Feb 27 Review for Mid-term exam Mar 1 Mid-term exam Mar 6 Ch 8 of L&G s book 9 Training and development analytics Additional reading materials from the Mar 8 instructor 10 Mar 13 Spring break Kaifeng Jiang HR Analytics Spring

13 Mar 15 Mar 20 Mar 22 Mar 27 Mar 29 Apr 3 Apr 5 Predicting employee performance Determining employee compensation Predicting employee attitudes 14 Apr 10 Introduction to advanced HR analytic techniques Apr 12 Final Presentations 15 Apr 17 Review for final exam Apr 19 Q&A 16 Apr 30 Accumulative final exam Ch 9 of L&G s book Ch 7 of E&E s book 2 nd Group assignment due Ch of L&G s book Additional reading materials from the instructor Data collection for final project due Additional reading materials from the instructor Additional reading materials from the instructor Pick-one research summary due Ch 11 of E&E s book Final project presentation due Final project report due Kaifeng Jiang HR Analytics Spring